kb22/Heart-Disease-Prediction
The project involves training a machine learning model (K Neighbors Classifier) to predict whether someone is suffering from a heart disease with 87% accuracy.
This project helps medical professionals or health data analysts quickly assess the likelihood of heart disease in patients. By inputting patient health metrics, it outputs a prediction of whether heart disease is present. This is designed for healthcare practitioners who need a rapid, data-driven initial screening tool.
266 stars. No commits in the last 6 months.
Use this if you are a clinician or health analyst looking for a quick, automated way to evaluate a patient's risk of heart disease based on their health data.
Not ideal if you need a diagnostic tool for definitive medical conclusions, as this is a predictive model, not a substitute for clinical judgment.
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266
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194
Language
Jupyter Notebook
License
MIT
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Last pushed
Mar 28, 2023
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